Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add renky1025/agent-skills --skill article-deconstructorgit clone --depth 1 https://github.com/renky1025/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/renky1025/agent-skills/article-deconstructor)<a href="https://agentmods.dev/skills/renky1025/agent-skills/article-deconstructor"><img src="https://agentmods.dev/badge/skills/renky1025/agent-skills/article-deconstructor.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00077 | $0.02156 |
| Opus 5 | $0.00039 | $0.01078 |
| Sonnet 5 | $0.00015 | $0.00431 |
| Haiku 4.5 | $0.00008 | $0.00216 |
Grade A, and why
article-deconstructor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 272 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Article Deconstructor - 文章拆解器
概述
将任意高流量文章拆解为核心要素，包括结构、观点、说服策略、情绪触发点和可复用的金句句式。
工作流程
用户提供文章
↓
全面拆解分析（10个维度）
↓
提取情绪价值句式
↓
提取刺痛观众句式
↓
对比分析句式模式
↓
输出结构化报告
拆解维度
执行拆解时，必须覆盖以下10个分析维度：
1. 核心观点
- 文章传递的单一核心信息是什么？
- 这个观点有何新颖性或反直觉性？
- 核心观点在文中出现了几次？位置在哪里？
2. 副观点/支撑论点
- 列出所有支撑核心观点的次级论点
- 每个副观点如何为核心观点服务？
- 副观点之间的逻辑关系是什么？（并列/递进/对比）
3. 说服策略
识别使用的说服技巧：
- 数据说服：具体数字、统计、研究引用
- 案例说服：故事、例子、个案分析
- 权威说服：专家、名人、机构背书
- 对比说服：前后对比、正反对比、极端对比
- 情感说服：恐惧、希望、愤怒、共鸣
- 逻辑说服：因果链、排除法、三段论
4. 情绪触发点
标记文中引发情绪反应的具体位置：
- 触发点位置（段落/句子）
- 触发情绪类型（焦虑/恐惧/希望/愤怒/共鸣/好奇）
- 触发机制（痛点揭示/身份认同/利益承诺）
5. 金句提取
提取所有值得收藏/传播的句子：
- 金句原文
- 金句类型（观点型/共鸣型/ actionable/反转型）
- 可复用的句式结构（用___表示可变部分）
6. 情感曲线分析
绘制读者情感波动轨迹：
- 开头情绪基线
- 文中情绪高点和低点位置
- 结尾情绪落点
- 情绪转折的具体触发点
7. 情感层次
分析情感表达的深浅递进：
- 表层：文字字面意思
- 中层：暗示的情感
- 深层：触及的人性本质
8. 论证方式多样性
统计并分类论证手法：
- 数据论证：X次
- 案例论证：X次
- 对比论证：X次
- 引用论证：X次
- 比喻/类比：X次
9. 视角转化分析
追踪文中视角切换：
- 第一人称（我）使用场景
- 第二人称（你）使用场景
- 第三人称（他/她/他们）使用场景
- 视角切换如何服务于说服目的？
10. 语言风格特征
总结独特语言印记：
- 句式偏好（短句/长句/排比/设问）
- 词汇偏好（专业术语/口语/网络语）
- 修辞手法（比喻/排比/对偶/反复）
- 节奏特征（快/慢/起伏）
句式提取
情绪价值句式
提取所有给读者带来正向情绪价值的句式：
- 认同感句式："原来不只是我这样..."
- 希望感句式："只要...就能..."
- 优越感句式："聪明人早就..."
- 归属感句式："我们都..."
- 成就感句式："你已经..."
格式：
原文：...
结构：[___的人，往往都___]
适用场景：...
刺痛观众句式
提取所有戳中读者痛点的句式：
- 焦虑唤醒："你还在...吗？"
- 恐惧放大："如果不...就会..."
- 后悔触发："要是早点..."
- 羞耻唤醒："大多数人..."
- 错失恐惧："已经有人..."
格式：
原文：...
结构：[___的人，正在___]
刺痛点：...
句式对比分析
对比两类句式的结构差异：
- 句式长度对比
- 主语倾向对比（主动/被动）
- 动词强度对比
- 情感极性对比（正向/负向）
- 使用位置对比（开头/中间/结尾）
输出格式
使用以下结构化模板输出：
# 文章拆解报告
## 文章信息
- 标题：
- 来源：
- 预估阅读量/点赞量：
- 目标受众：
## 一、核心架构
### 核心观点
[一句话总结]
### 副观点清单
1. ...
2. ...
3. ...
### 观点递进逻辑
[描述观点如何层层推进]
## 二、说服策略矩阵
| 策略类型 | 使用次数 | 具体位置 | 效果评估 |
|---------|---------|---------|---------|
| 数据说服 | X次 | 第X段 | 高/中/低 |
| ... | ... | ... | ... |
## 三、情绪触发地图
### 触发点1
- 位置：第X段
- 原文："..."
- 触发情绪：
- 触发机制：
### 触发点2
...
## 四、金句库
### 观点型金句
1. 原文："..."
结构：[___]
适用场景：...
### 共鸣型金句
...
## 五、情感曲线
[用文字描述或简单ASCII图表]
开头(情绪A) → 触发点1(情绪B) → 触发点2(情绪C) → 结尾(情绪D)
## 六、句式宝库
### 情绪价值句式（共X句）
1. 原文："..."
结构：[___]
情绪类型：
### 刺痛观众句式（共X句）
1. 原文："..."
结构：[___]
痛点类型：
### 句式对比洞察
- 情绪句式平均长度：X字
- 刺痛句式平均长度：X字
- 情绪句式多用：[动词/形容词/名词]
- 刺痛句式多用：[动词/形容词/名词]
## 七、可复用的写作模板
### 开头模板
[提炼可复用的开头结构]
### 论证模板
[提炼可复用的论证结构]
### 结尾模板
[提炼可复用的结尾结构]
## 八、学习要点
### 值得借鉴的3个技巧
1. ...
2. ...
3. ...
### 可避免的2个问题
1. ...
2. ...
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 272 lines · 77 tokens per session scan A ea8b300d8dc0
article-deconstructor is a skill published in the GitHub repository renky1025/agent-skills (10 stars, last pushed 9d ago), licensed MIT. It adds 77 tokens to every session and 2,156 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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